1. Field of the Invention
The present invention relates to semiconductor devices and, in particular, to a process employing a stochastic search algorithm to determine model parameters for MOSFETs.
2. Description of Related Art
In order to achieve increased performance metal oxide semiconductor field effect transistors (MOSFETs) at ever decreasing line width, for example, at one-quarter micron foundry technology now being used for manufacturing semiconductor devices, it is critical to employ accurate modeling while creating the initial designs of such MOSFETs. There are several commercial software packages available to solve the specific problem of semiconductor device modeling, for example, the UTMOST modeling software available from Silvaco Data Systems, Santa Clara, Calif. Additionally, proprietary software has also been developed by many companies to solve this problem. In all the known approaches, a great amount of human interaction is required in the fitting process.
The modeling software generally performs only a local optimization and, accordingly, may not find a global minimum unless reruns are made with several different initial guesses. Furthermore, the modeling software is not able to provide a measure of the fit of the overall model because of the wide range of magnitudes of currents in different regions of operation. Therefore, an operator must perform successive optimizations in different regions and iterate through the successive regions until overall convergence is obtained. Existing software does not evaluate reasonableness of values beyond the limits of the measured data until after fitting the data. If problems are found at that time, then additional iterations are required.
Although U.S. Pat. No. 5,136,686 teaches the application of genetic algorithms to model fitting, there is no disclosure or suggestion that it may be applied to the problem of fitting models for circuit simulation, particularly for modeling MOSFETs. Moreover, this patent defines the fitness function as the sum of the distances in the model range space between each pair of measured and simulated points. For semiconductor devices, the model output varies by many orders of magnitude such that only error regions of high output values contribute significantly to the sum. Other areas are not well modeled because the fitness function does not adequately reflect the fit in small valued regions.
Additionally, it has been found to be important that a fitness function also include a measure of the physical reasonableness of the model in regions where actual data cannot be measured, because the device will not operate there. Such constraints are important for models which will be used in complex computer simulations because violating them can lead to failure of the simulations to converge.
Bearing in mind the problems and deficiencies of the prior art, it is therefore an object of the present invention to provide an improved method of determining modeling parameters for MOSFETs.
It is another object of the present invention to provide a MOSFET modeling algorithm which may achieve both global and local optimization.
A further object of the invention is to provide a method of determining model parameters for MOSFETS which requires less human interaction is required in the fitting process.
It is yet another object of the present invention to provide a method of determining a set of parameters for modeling a MOSFET which provides a measure of the fit of the overall model over a wide range of magnitudes of currents in different regions of operation.
It is another object of the present invention to provide a method of calculating certain critical parameters which may limit the size of the search space.
Still other objects and advantages of the invention will in part be obvious and will in part be apparent from the specification.